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Huan Liu

题目:Blog Communities and Influential Bloggers

报告人:Huan Liu
        Associate professor
        Arizona State University.

时间:6月20日(星期五) 10:00-11:00

地点:蒙民伟楼404会议室

摘要:Blogging becomes a popular way for a Web user to publish information on
the Web. Bloggers write blog posts, share their likes and dislikes, voice thei
r opinions, provide suggestions, report news, and form groups in Blogosphere.
Bloggers form their virtual communities of similar interests. Activities happe
ned on Blogosphere affect the external world. One way to understand the develo
pment on Blogosphere is to find influential blog sites. There are many non-inf
luential blog sites which form "the long tail". Regardless of a blog site bein
g influential or not, there are influential bloggers. Inspired by the high imp
act of the influentials in a physical community, we study a novel problem of i
dentifying influential bloggers at a blog site. Active bloggers are not necess
arily influential. Influential bloggers can impact fellow bloggers in various
ways. In this work, we discuss the challenges of identifying influential blogg
ers, investigate what constitutes influential bloggers, present a preliminary
model attempting to quantify an influential blogger, and pave the way for buil
ding a robust model that allows for finding various types of the influentials.
 To illustrate these issues, we conduct experiments with data from a real-worl
d blog site, evaluate multi-facets of the problem of identifying influential b
loggers, and discuss unique challenges. We conclude with interesting findings
and future work.

简历:Huan Liu is an associate professor of Computer Science and Engineering a
t Arizona State University. He received his Ph.D. from University of Southern
California, researched at Telecom Research Labs in Australia, and taught at Na
tional University of Singapore. He has been a visiting scholar at Microsoft Re
search Asia, a consultant of AOL, a summer faculty fellow at Motorola Research
 Lab and at Air Force Research Lab, and was invited to Google Faculty Summit (
Summer 2008). His research interests are in data/web mining, machine learning,
 social computing, and artificial intelligence. These include search and optim
ization problems that arise in many real-world applications with high-dimensio
nal data of disparate forms such as text categorization, streaming data summar
ization, biomarker identification, and text/web mining. His research covers ef
ficient search algorithms, semi-supervised models, spectral analysis methods,
bias analysis, and experiment and evaluation methodologies. The research is be
ing expanded to taxonomy-based group profiling, searching for influential blog
gers in a community, information integration of multiple data sources, trust a
nd reputation of multi-source information, and predicting high-cost patients i
n healthcare domains. His well-cited publications include books, book chapters
, encyclopedia entries as well as conference and journal papers. His former gr
aduate students have been professors at research universities and employed by
Amazon, Google, Microsoft, and Yahoo, among others. He is a co-organizer of th
e International Workshop Series on Social Computing, Behavioral Modeling, and
Prediction in Phoenix, AZ (SBP’08 and SBP’09), a conference co-chair of the
12th Pacific Asia Conference on Knowledge Discovery and Data Mining in  Osaka,
 Japan (PAKDD’08), and a program committee co-chair of the SIAM International
 Conference on Data Mining (SDM’09 http://www.siam.org/meetings/sdm09) in Ren
o Area, Nevada.



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